sponsored byIEEEACMThe International Conference for High Performance 
Computing, Networking, Storage and Analysis
FacebookTwitterGoogle PlusLinkedInYouTubeFlickr

SCHEDULE: NOV 16-21, 2014

When viewing the Technical Program schedule, on the far righthand side is a column labeled "PLANNER." Use this planner to build your own schedule. Once you select an event and want to add it to your personal schedule, just click on the calendar icon of your choice (outlook calendar, ical calendar or google calendar) and that event will be stored there. As you select events in this manner, you will have your own schedule to guide you through the week.

Compiler Techniques for Massively Scalable Implicit Task Parallelism

SESSION: Compiler Analysis and Optimization

EVENT TYPE: Papers

TIME: 4:00PM - 4:30PM

SESSION CHAIR: Milind Kulkarni

AUTHOR(S):Timothy G. Armstrong, Justin M. Wozniak, Michael Wilde, Ian Foster

ROOM:393-94-95

ABSTRACT:

Swift/T is a high-level language for writing concise, deterministic scripts that compose serial or parallel codes implemented in lower-level programming models into large-scale parallel applications. It executes using a data-driven task parallel execution model that is
capable of orchestrating millions of concurrently executing asynchronous tasks on
homogeneous or heterogeneous resources.

Producing code that efficiently executes at this scale requires sophisticated compiler transformations: poorly optimized code inhibits scaling with excessive synchronization and communication. We present a comprehensive set of compiler techniques for data-driven task parallelism, including novel compiler optimizations and intermediate representations. We report application benchmark studies, including unbalanced tree search and simulated annealing, and demonstrate that our techniques greatly reduce communication overhead and enable extreme scalability, distributing up to 612 million dynamically load balanced tasks per second at scales of up to 262,144 cores without explicit parallelism, synchronization,
or load balancing in application code.

Chair/Author Details:

Milind Kulkarni (Chair) - Purdue University

Timothy G. Armstrong - University of Chicago

Justin M. Wozniak - Argonne National Laboratory

Michael Wilde - University of Chicago and Argonne National Laboratory

Ian Foster - University of Chicago and Argonne National Laboratory

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar


Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society